AI Automation EngineerRole Type: Full-time | Location: Onsite | Stack: Python
About the RoleThe Company We are building a vertically integrated, AI-native operating platform for institutional real estate investment. The platform automates and connects every stage of the investment lifecycle from acquisition through renovation, leasing, and refinance replacing manual processes with code, AI, and SaaS integrations. Remote-first, no on-ground employees.
How We Build Software We follow an automation-first hierarchy: code first, then specialized AI, then LLMs, then offshore humans, then US contractors. Humans are the last resort, not the first option. All feature work follows a spec-driven development approach. You write specs, orchestrate Claude Code agents, review output, and iterate. You are an engineer who directs AI, not a typist who writes every line by hand. If you think what took an hour still takes an hour or AI coding tools are a gimmick, this is not the role.
What You'll Do- Build and deploy AI agents and automation workflows for real estate operations (underwriting, document processing, lead qualification, contractor coordination, etc.)
- Design multi-step agent architectures with tool-calling, structured outputs, retries, fallbacks, and human-in-the-loop escalation
- Build Python microservices that expose AI capabilities via REST APIs to the main platform
- Implement cost management and token optimization across all LLM usage
- Convert manual/human tasks into AI-automated workflows based on detailed process specs
- Work with the product team to identify which of our 178 mapped tasks can be shifted from Human to AI
- Monitor, evaluate, and improve agent performance with metrics and logging
Requirements- 5+ years professional Python backend engineering (not scripting or notebooks)
- Production experience with LLM APIs (OpenAI, Anthropic, etc.) not demos or tutorials
- Experience with agent frameworks (LangChain, CrewAI, AutoGen, or custom)
- Strong understanding of structured outputs, function/tool calling, and prompt engineering for deterministic behavior
- Experience designing and deploying microservices with REST APIs
- Ability to build robust error handling, retry logic, and fallback patterns for non-deterministic AI systems
- Cost-aware: experience managing token budgets and optimizing LLM spend
- Comfortable with remote async work across time zones
- Spec-driven mindset: can take a detailed process spec and translate it into working automation
Nice to Have- Experience with real estate, proptech, or financial services automation
- Familiarity with RAG (Retrieval Augmented Generation) pipelines
- Experience with document parsing/extraction (OCR, PDF processing)
- Knowledge of vector databases (Pinecone, Weaviate, pgvector)
- Experience with Claude Code or similar AI-assisted development workflows
This Role Is NOT- A fullstack/frontend role you will not build UI or work on the Next.js platform
- A data science or ML training role we use pre-trained LLMs, not custom models
- A no-code automation role this is real engineering, not Zapier workflows
- A research role you ship production systems, not papers
